Advanced driver functions in vehicles rely on accurate maps from which a prediction may be made about how the upcoming route of the vehicle will look like.
A map may be provided by a third party. Such map comprises information that make it possible to generate a prediction of how the road ahead of the vehicle will look like in terms of road slope. This prediction is of interest since certain functions rely on information about the upcoming road at a further distance than sensors such as radar or cameras can provide. Such functions can be used to save fuel by calculating an optimal velocity profile for the vehicle. By having such a map many other functions can be realized.
The maps used today are static, i.e. they are not updated once the vehicle is delivered. Thus vehicle maps may therefore lack coverage in certain countries where accurate map data is not available or just on smaller roads which are too uneconomical to map.
Further, recently built roads may not be comprised on such map. Additionally, some particular environments may be very dynamical such as e.g. mines, building sites, deforestation areas, storage areas in a harbor, a load terminal or similar.
It is thus a problem for a driving control unit in a vehicle to get appropriate map information, corresponding to the geographical environment, in order to make correct predictions of the vehicle route.
Document DE102010042065 describes a method for combining route network data from a digital map with data of a digital terrain model. The network data represents coordinates and curvature of the road and the model represents geodetic height information. However, no prediction of the route of the vehicle may be made, in case there is no road on the digital map, or no digital map at all. Further the document does not discuss estimation of route distance using statistic data.
Documents US2010114474 and US2010324752 disclose methods for calculating surface elevation of the road in relation to distance of the route to be travelled by a vehicle. However, no prediction of the route of the vehicle may be made, in case there is no road on the digital map, or no digital map at all. Further the documents do not discuss estimation of route distance using statistic data.
Document EP2623932 discloses a method of creating a route of a vehicle using a grid net, where measurements are made at each grid of the net. However, no prediction of the route of the vehicle may be made, in case there is no road on the digital map, or no digital map at all.
Document JP3966097 discloses a vehicular road surface altitude estimation device that estimates the altitude of a travel route based on linear interpolation. However, no prediction of the route of the vehicle is made, in case there is no road on the digital map, or no digital map at all.
It may thereby be desired to be able to create and continuously update a map and provide a solution to the above discussed problems in connection with vehicle route prediction.